Abstract

Different classes of organic matter (OM) have been systematically investigated in sediments and suspended particulate matter (SPM) along the Danube River in order to understand causes of compositional changes. Analytical pyrolysis revealed the dominance of natural organic matter (NOM) in most of the samples. The predominance of aquatic biomass is evident mainly from the abundance of organonitrogen compounds and phenol distributions. As the river enters a forested gorge, the terrestrial component of the NOM in sediments is more significant. This is reflected in abundant methoxyphenols and a very high carbon preference index. SPM sample from a tributary shows a unique geochemical signature. It contains abundant carboxylic acids, amines, isoprenoids in the pyrolyzate, and is dominated by phytol and 24-methyl-cholesta-5,24(28)-dien-3β-ol in the extract, produced by a diatom bloom. Wax esters with a relatively high proportion of short, methyl-branched alkyl-chains appear together with abundant phytadienes and n-C 17 alkane in some samples, suggesting a microbial origin. Anthropogenic OM from runoff and atmospheric deposition was evident from a minor input of polycyclic aromatic hydrocarbons (PAHs) originating from mixed combustion sources. Multivariate analysis using PAH data led us to define simple molecular ratios to distinguish the PAH composition in sand and silty sediments. The newly defined ratios are the alkylated phenanthrenes and anthracenes ratio (APA; C 1-C 3/C 0–C 3 phenanthrenes and anthracenes) and the PAH ring number ratio (RN; 5–6 ring parent PAHs/all parent PAHs). This demonstrates that alkylated, as well as 5–6 ring PAHs are better preserved in the finer than in coarser grained sediments. A ubiquitous, but minor input of petroleum-related contamination with a uniform composition was evident in all samples as revealed by the analysis of petroleum biomarkers. This study demonstrates that the investigation of different classes of riverine OM requires a detailed molecular analysis, applying a series of analytical techniques and adequate statistical data treatment.

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